In MDAI we are particularly interested in the different facets of decision processes in a broad sense. This includes model building and all kind of mathematical tools for data aggregation, information fusion, and decision making; tools to help decision in data science problems (including e.g., statistical and machine learning algorithms as well as data visualization tools); and algorithms for data privacy and transparency-aware methods so that data processing processes and decisions made from them are fair, transparent and avoid unnecessary disclosure of sensitive information.

The MDAI conference includes tracks on the topics of (i) data science, (ii) data privacy, (iii) aggregation funcions, (iv) human decision making, (v) graphs and (social) networks, and (vi) recommendation and search. The conference has been since 2004 a forum for researchers to discuss last results into these areas of research.

MDAI is rated as a CORE B conference by the Computing Research and Education Association of Australasia - CORE.

Publication:

Proceedings with accepted papers will be published in the LNAI/LNCS series (Springer-Verlag) and distributed at the conference, as done in previous conferences. See LNAI volumes in Springer: 3131, 3558, 3885, 4617, 5285, 5861, 6408, 6820, 7647, 8234, 8825, 9321, 9880, 10571, 11144. Acceptance rate in 2018: 24/43.

Besides, papers, that according to the evaluation of the referees, are not suitable for the LNAI but that have some merits will be published in a USB proceedings and scheduled in the MDAI program. Direct submission for the USB proceedings is also possible. We have a later deadline for direct submission for the USB proceedings.

Topics of interest:

Original papers in the areas mentioned above are sought. More detailed information on the tracks of the conference here.